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相关概念视频

Decision Making: P-value Method01:09

Decision Making: P-value Method

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The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
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Expected Value01:15

Expected Value

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The expected value is known as the "long-term" average or mean. This means that over the long term of experimenting over and over, you would expect this average. The expected average is represented by the symbol μ. It is calculated as follows:
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One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

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This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
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Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

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A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
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The Availability Heuristic01:08

The Availability Heuristic

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A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):
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Testing a Claim about Standard Deviation01:19

Testing a Claim about Standard Deviation

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A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
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Updated: Sep 19, 2025

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
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在价值测试概率权衡的情况下,研究时间分配是基于预期最大化吗?

Hui Xu1, Yue Chu1, Xiuya Li1

  • 1Faculty of Psychology, Tianjin Normal University, Tianjin, 300387, China.

Psychological research
|June 3, 2025
PubMed
概括

面临入学考试时间限制的学习者不仅仅使用预期分数来分配学习时间. 他们优先考虑中等价值的项目,表明了超出简单的预期效用范围的复杂决策过程.

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科学领域:

  • 认知心理学 认知心理学
  • 教育心理学教育心理学
  • 决策科学 决策科学 决策科学

背景情况:

  • 学习者经常面临考试准备的时间有限.
  • 有效的研究时间分配需要平衡项目得分和测试概率.
  • 预期效用等现有理论可能无法完全捕捉现实世界的学习行为.

研究的目的:

  • 研究学习者如何在各种限制下分配有限的学习时间.
  • 检查项目特征 (分数,概率,难度) 对学习时间分配的影响.
  • 测试预期效用理论在学习环境中的适用性.

主要方法:

  • 三个实验进行了不同的时间限制和项目类型 (低得分-高概率,高得分-低概率,中等得分-中等概率).
  • 参与者将学习时间分配给不同的项目.
  • 在实验2中操纵了项目难度,在实验3中延长了时间限制.

主要成果:

  • 参与者将最多的时间分配给中等分数-中等概率项目.
  • 研究时间的分配不仅仅是基于预期的分数,即使项目难度和时间限制不同.
  • 结果与来自预期效用理论的预测相矛盾.

结论:

  • 学习者的学习时间分配受到超出简单预期分数的因素的影响.
  • 在时间限制下的决策涉及比预期效用理论预测的更复杂的策略.
  • 未来的研究应该探索其他影响学习时间分配的认知因素.